mirror of
https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nopaque.git
synced 2025-01-14 12:10:35 +00:00
53 lines
4.1 KiB
Django/Jinja
53 lines
4.1 KiB
Django/Jinja
<div id="data-processing-and-analysis-modal" class="modal">
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<div class="modal-content">
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<div class="card-panel primary-color white-text">
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<h4 class="m-3"><i class="material-icons left" style="font-size: inherit; line-height: inherit;">miscellaneous_services</i>Data Processing & Analysis</h4>
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</div>
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<br>
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<div class="row">
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<div class="col s12 m6 l3 center-align hoverable" style="position: relative;">
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<a href="{{ url_for('services.file_setup_pipeline') }}" style="position: absolute; width: 100%; height: 100%; top: 0; left: 0;"></a>
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<i class="large nopaque-icons service-icons service-color-text text-darken" data-service="file-setup-pipeline"></i>
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<br>
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<b class="service-color-text text-darken" data-service="file-setup-pipeline">File Setup</b>
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<p class="light">Digital copies of text based research data (books, letters, etc.) often comprise various files and formats. nopaque converts and merges those files to facilitate further processing and the application of other services.</p>
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</div>
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<div class="col s12 m6 l3 center-align center-align hoverable" style="position: relative;">
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<a href="{{ url_for('services.tesseract_ocr_pipeline') }}" style="position: absolute; width: 100%; height: 100%; top: 0; left: 0;"></a>
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<i class="large nopaque-icons service-icons service-color-text text-darken" data-service="tesseract-ocr-pipeline"></i>
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<br>
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<b class="service-color-text text-darken" data-service="tesseract-ocr-pipeline">Optical Character Recognition</b>
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<p class="light">nopaque converts your image data – like photos or scans – into text data through OCR making it machine readable. This step enables you to proceed with further computational analysis of your documents.</p>
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</div>
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{% if config.NOPAQUE_TRANSKRIBUS_ENABLED %}
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<div class="col s12 m6 l3 center-align center-align hoverable" style="position: relative;">
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<a href="{{ url_for('services.transkribus_htr_pipeline') }}" style="position: absolute; width: 100%; height: 100%; top: 0; left: 0;"></a>
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<i class="large nopaque-icons service-icons service-color-text text-darken" data-service="transkribus-htr-pipeline"></i>
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<br>
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<b class="service-color-text text-darken" data-service="transkribus-htr-pipeline">Transkribus HTR Pipeline</b>
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<p class="light">nopaque converts your image data – like photos or scans – into text data through HTR making it machine readable. This step enables you to proceed with further computational analysis of your documents.</p>
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</div>
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{% endif %}
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<div class="col s12 m6 l3 center-align center-align hoverable" style="position: relative;">
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<a href="{{ url_for('services.spacy_nlp_pipeline') }}" style="position: absolute; width: 100%; height: 100%; top: 0; left: 0;"></a>
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<i class="large nopaque-icons service-icons service-color-text text-darken" data-service="spacy-nlp-pipeline"></i>
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<br>
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<b class="service-color-text text-darken" data-service="spacy-nlp-pipeline">Natural Language Processing</b>
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<p class="light">By means of computational linguistic data processing (tokenization, lemmatization, part-of-speech tagging and named-entity recognition) nopaque extracts additional information from your text.</p>
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</div>
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<div class="col s12 m6 l3 center-align center-align hoverable" style="position: relative;">
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<a href="{{ url_for('services.corpus_analysis') }}" style="position: absolute; width: 100%; height: 100%; top: 0; left: 0;"></a>
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<i class="large nopaque-icons service-icons service-color-text text-darken" data-service="corpus-analysis"></i>
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<br>
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<b class="service-color-text text-darken" data-service="corpus-analysis">Corpus analysis</b>
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<p class="light">nopaque lets you create and upload as many text corpora as you want. It makes use of CQP Query Language, which allows for complex search requests with the aid of metadata and NLP tags.</p>
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</div>
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</div>
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</div>
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<div class="modal-footer">
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<a class="btn-flat modal-close">Close</a>
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</div>
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</div>
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